CN103617552A - Power generation cost optimization method for iron and steel enterprise - Google Patents

Abstract

The invention provides a power generation cost optimization method for an iron and steel enterprise, and belongs to the technical field of comprehensive power saving in iron and steel enterprises. The power generation cost optimization method comprises the following steps: a dispatching cycle T which needs power generation cost optimization is determined, and power generation cost optimization parameters of a set are acquired; a network cross section used for planning a current power generation schedule is acquired; fuel cost of the generator set under the condition of coal gas blending combustion in the cycle is determined; according to the energy consumption of the set of the iron and steel enterprise, external electricity purchasing cost and an external power transmission income physical truth, an optimized dispatching model which aims for the lowest power generation cost of a whole system is established; results of self-generating set output, externally purchased electricity, externally transmitted electric quantity and the like of the iron and steel enterprise are obtained according to an optimization solution. The power generation cost optimization method for the iron and steel enterprise has the advantages of being capable of meeting requirements for production loads, generator set output, line transmission capacity and the like, guaranteeing safe and reliable operation of a grid of the iron and steel enterprise, further optimizing and adjusting self-generating electricity output and a proportional relation between self-generated electricity and externally purchased electricity in combination with a load prediction curve and a production and repair schedule, and enabling the generation cost of the iron and steel enterprise to be the lowest.

Description

The method that a kind of iron and steel enterprise cost of electricity-generating is optimized

Technical field

The invention belongs to iron and steel enterprise's integrated power-saving technical field, the method that particularly provides a kind of iron and steel enterprise cost of electricity-generating to optimize.

Background technology

Electric power is the important energy of iron and steel enterprise, and it accounts for 20% in iron and steel energy consumption structure.Some motor devices as the heating of (motor, fan blower, compressor etc.), process and other process engineerings in, all need electric power resource.Source form two aspects of iron and steel enterprise's electric power: self power generation and outer power purchase.Self power generation is mainly that private station and the residual heat and energy of enterprises recycled generating, increasing although the spontaneous electric weight of enterprise accounts for total electricity consumption proportion, but still need to buy a large amount of electric energy from external power grid.

Due to the singularity of iron and steel enterprise's electric system, iron and steel enterprise has certain potentiality aspect reduction power supply cost, and on the one hand, because outer power purchase is to adopt crest paddy to put down to carry out pricing for segment, the flat self power generation rate of rational crest paddy, can reduce outer power purchase cost greatly; Inner generators that generally have many group paired runnings of ， iron and steel enterprise on the other hand, the capacity of these units is different, and its economic load scope is just likely different, even the unit of same model, economic benefit is separately difference to some extent also.Therefore meeting under power grid security, high-quality service condition, to the burden with power of the genset science of carrying out, distributing the cost of ，Neng Shi enterprise generating minimum, enterprise obtain economic benefit maximum.

At present, for the research of cost of electricity-generating Optimized Operation, be all to concentrate on fuel-burning power plant according to the energy consumption model optimization of unit, to calculate to realize and reduce coal consumption object, or realize energy-saving and cost-reducing by the Load optimal allocation between genset.And the research of optimizing for the cost of electricity-generating of enterprise self electrical network is less, part is only, by experience or Pinggu, peak electricity price, genset power curve is manually set, but due to the electric system multi-user of iron and steel enterprise (comprising a large amount of impact loads), many fuel source (by-product gas, outsourcing coal), multi-voltage grade, multi-state changes the (production schedule, turnaround plan), and electric system with technological process contact closely, the recovery of part power source residual heat and energy in operation production run and conversion are (as TRT, CDQ), the features such as part power fuel source operation by-product gas, the generation schedule of rule of thumb setting can be met difficulty when reality is carried out, in addition, experience scheduling is the safety of taking into account system effectively, the operating scheme reality obtaining is often infeasible, need to repeatedly adjust, thereby be difficult to guarantee security and the economy of operation, and bring huge workload to dispatcher.

Therefore, the task such as produce in order to meet enterprise that load needs, genset are exerted oneself, circuit transmission capacity, industry are bled, guarantee under the safe and stable operation prerequisite of enterprise's electrical network simultaneously, analyze coal gas and mix the feature of the genset energy consumption of burning, consider the income of outer power purchase cost and outer power transmission, in conjunction with enterprise's load prediction curve, the production schedule, turnaround plans etc., optimize the unit output plan that calculates cost of electricity-generating minimum, provide the scheme of more economically viable self power generation operation.

Summary of the invention

The method that the object of the present invention is to provide a kind of iron and steel enterprise cost of electricity-generating to optimize, can meet tasks such as producing load needs, genset are exerted oneself, circuit transmission capacity, guarantee the safe and stable operation of enterprise's electrical network simultaneously, in conjunction with load prediction curve, produce and turnaround plan, further optimize and revise self power generation and exert oneself, and the proportionate relationship ，Shi enterprise cost of electricity-generating of self power generation and outer power purchase is minimum.

The present invention includes following steps:

Step 1, determine T dispatching cycle that need to carry out cost of electricity-generating optimization, obtain unit generation cost optimization parameter, these parameters comprise: enterprise's load prediction curve, production and turnaround plan, the plan of outsourcing power transmission, the start and stop state of unit, upstate, the plan of exerting oneself of fixing genset in dispatching cycle, the plan of capable of regulating unit output;

Step 2, obtain the network section for generation schedule establishment a few days ago, network section refers to the one group of transmission line of electricity (can be also transformer or generator etc.) that is mutually related in power grid security or electric weight transaction, simultaneously in conjunction with enterprise's production maintenance plan, utilize electric network model automatically to generate the network topology of day part, and calculate the trend distribution of day part and monitor element influence coefficient;

Step 3, determine that in the cycle, consideration coal gas is mixed the genset fuel cost in burning situation:

$C_{\mathrm{zf}}=\underset{t=1}{\overset{N}{\mathrm{\Σ}}}[F{\left(P\right)}_{i,t}\×C_{i,t}^f]$

F(P) _i,t＝aP _i,t ²+bP _i,t+c

Wherein, C _zffor genset fuel cost, F (P) _i,tbe the mark coal consumption of i platform unit t period, P _i,tbe meritorious the exerting oneself of i platform unit t period,

be the fuel unit price of i platform unit t period coal and coal gas mixed combustion, C ^coal, C ^bfg, C ^cogbe respectively outsourcing coal, blast furnace gas, the price of coke-oven gas; Q ^coal, Q ^bfg, Q ^cogbe respectively coal, blast furnace gas, the calorific value of coke-oven gas; Q wherein ^bfor mark coal calorific value, its value is constant is 29308KJ/Kg;

be respectively i platform unit t period coal, blast furnace gas, coke-oven gas accounts for the ratio of total fuel heat.

Consider that coal gas is mixed in the existing system of situation ，Cong enterprise of burning and read coal, blast furnace gas, the amount of coke-oven gas with and corresponding the meritorious of unit exert oneself, by coal, blast furnace gas, coke-oven gas is amounted to into mark coal amount, and then matching obtains the units consumption model F (P) in one-period T _i,t=aP _i,t ²+ bP _i,t+ c is a wherein, b, and c is fitting coefficient;

Step 4, according to enterprise's units consumption, outer power purchase cost and outer power transmission income actual conditions are set up and be take the Optimal Operation Model that total system cost of electricity-generating minimum is target; Using 15 minutes logic periods as an optimization, using dispatching cycle internal loading prediction curve as research object, in conjunction with producing and turnaround plan, optimize enterprises and can dispatch exerting oneself of genset, optimization aim is enterprise's self power generation cost minimization.

Iron and steel enterprise's cost of electricity-generating Optimized model is, objective function:

$\min C_{\cos t}=\underset{t}{\mathrm{\Σ}}(\underset{i=1}{\overset{K}{\mathrm{\Σ}}}{C}_{\mathrm{zf}(i,t)}+C_{\mathrm{wg}}-C_{\mathrm{ws}})$

Constraint condition:

$C_{\mathrm{wg}}=\underset{t}{\mathrm{\Σ}}{P}_{w,t}\×C_t\×{\mathrm{\δ}}_t$

$C_{\mathrm{ws}}=\underset{t}{\mathrm{\Σ}}{P}_{\mathrm{ws},t}\×C_s\×{\mathrm{\σ}}_t$

$\underset{i=1}{\overset{K}{\mathrm{\Σ}}}{P}_{i,t}+P_{w,t}=P_{\mathrm{load},t}$

P _i,min≤P _i,t≤P _i,max

-UR _i≤P _i,t-P _i,t-1≤UR _i,i＝1,2...K

$P_{\mathrm{ij},t}=\underset{i\∈M}{\mathrm{\Σ}}[P(i,t)-S_{i,t}]{\mathrm{\ω}}_{i,j,t}$

P _ij,min≤P _ij,t≤P _ij,max

$P_{w,\min }\≤\underset{t=1}{\overset{24}{\mathrm{\Σ}}}{P}_{w,t}\≤P_{w,\max }$

Wherein, K is schedulable power plant for self-supply genset number in enterprise, and N is the time hop count comprising in system dispatching cycle T, C _{zf (i, t)}be the self power generation cost of i platform unit t period, C _wgouter power purchase cost, P _w,touter purchase of electricity, C _tfor the outsourcing electricity price of t period, δ _tbe that 0,1 scale is levied and had or not outer power supply, C _wsouter power transmission income, P _{ws, t}send electric weight outside, C _sfor sending electricity price outside, σ _tbe that 0,1 scale is levied without outer power transmission, P _i,tfor meritorious the exerting oneself of i platform unit t period, P _{load, t}for t period enterprise load prediction value, P _{i, min}, P _{i, max}be respectively unit i and exert oneself and bound ,-UR _i, UR _ifor per period of unit i can load increase and decrease maximal value (climbing capacity of unit), P _{ij, t}for branch road ij at t the trend on the time period, P (i, t) is node i at the injecting power of t time period, M is the supervision parts number comprising under node i, S _i,tfor node load power, ω _{i, j, t}for node injecting power to branch road ij at t the influence coefficient on the time period, P _{ij, min}, P _{ij, max}the bound that represents branch road ij trend, P _{w, min}, P _{w, max}do not represent the confession purchase of electricity bound that generator i is determined by contract in time T;

Step 5, according to Optimization Solution, obtaining enterprise's self generating sets exerts oneself, outer purchase of electricity, send the result of electric weight outside, consider that overall network monitors element, carries out Security Checking to day part, if not newly-increased, monitor that element voltage or electric current are out-of-limit, enter step 6, otherwise calculate the influence coefficient information of newly-increased out-of-limit supervision element, then enter step 2;

Step 6, iteration finishes, and draws iron and steel enterprise's self power generation plan, optimizes and finishes, and provides the self power generation scheme of cost minimization.

The invention has the beneficial effects as follows:

The iron and steel enterprise's cost of electricity-generating Optimization Scheduling that adopts the present invention to propose, can arranged rational the generation schedule of following enterprise private station, the present invention has considered enterprise's self power generation, outer power purchase, outer power transmission for the impact of cost of electricity-generating, consider the various constraint conditions such as Constraints of Equilibrium, the constraint of genset self-operating, outsourcing Constraint and electric power netting safe running constraint when system is moved a few days ago simultaneously, guaranteed the enforceability of generation schedule; Taking into account system load prediction curve of the present invention, production maintenance plan, Pinggu, outer power purchase peak electricity price gap, the situations such as outer power transmission income, optimize the plan of exerting oneself of enterprise's self generating sets, guaranteed that enterprise's private station stablizes economical operation under prerequisite meeting security of system.

Accompanying drawing explanation

Fig. 1 is the FB(flow block) of iron and steel enterprise of the present invention cost of electricity-generating optimization method.

Embodiment

Below in conjunction with accompanying drawing, the present invention will be further described

Refer to Fig. 1, the method that iron and steel enterprise of the present invention cost of electricity-generating is optimized, can meet tasks such as producing load needs, genset are exerted oneself, circuit transmission capacity, guarantee the safe and stable operation of enterprise's electrical network simultaneously, in conjunction with load prediction curve, produce and turnaround plan, further optimize and revise self power generation and exert oneself, and the proportionate relationship ，Shi enterprise cost of electricity-generating of self power generation and outer power purchase is minimum.The method of described iron and steel enterprise cost of electricity-generating optimization comprises the following steps:

The present invention includes following steps:

Step 1, determine T dispatching cycle that need to carry out cost of electricity-generating optimization, obtain unit generation cost optimization parameter, these parameters comprise: enterprise's load prediction curve, production and turnaround plan, the plan of outsourcing power transmission, the start and stop state of unit, upstate, the plan of exerting oneself of fixing genset in dispatching cycle, the plan of capable of regulating unit output;

Step 2, obtain the network section for generation schedule establishment a few days ago, network section refers to the one group of transmission line of electricity (can be also transformer or generator etc.) that is mutually related in power grid security or electric weight transaction, simultaneously in conjunction with enterprise's production maintenance plan, utilize electric network model automatically to generate the network topology of day part, and calculate the trend distribution of day part and monitor element influence coefficient;

Step 3, determine that in the cycle, consideration coal gas is mixed the genset fuel cost in burning situation:

$C_{\mathrm{zf}}=\underset{t=1}{\overset{N}{\mathrm{\Σ}}}[F{\left(P\right)}_{i,T}\×C_{i,t}^f]$

F(P) _i,t＝aP _i,t ²+bP _i,t+c

Wherein, C _zffor genset fuel cost, F (P) _i,tbe the mark coal consumption of i platform unit t period, P _i,tbe meritorious the exerting oneself of i platform unit t period,

be the fuel unit price of i platform unit t period coal and coal gas mixed combustion, C ^coal, C ^bfg, C ^cogbe respectively outsourcing coal, blast furnace gas, the price of coke-oven gas; Q ^coal, Q ^bfg, Q ^cogbe respectively coal, blast furnace gas, the calorific value of coke-oven gas; Q wherein ^bfor mark coal calorific value, its value is constant is 29308KJ/Kg;

be respectively i platform unit t period coal, blast furnace gas, coke-oven gas accounts for the ratio of total fuel heat.

Consider that coal gas is mixed in the existing system of situation ，Cong enterprise of burning and read coal, blast furnace gas, the amount of coke-oven gas with and corresponding the meritorious of unit exert oneself, by coal, blast furnace gas, coke-oven gas is amounted to into mark coal amount, and then matching obtains the units consumption model F (P) in one-period T _i,t=aP _i,t ²+ bP _i,t+ c is a wherein, b, and c is fitting coefficient;

Step 4, according to enterprise's units consumption, outer power purchase cost and outer power transmission income actual conditions are set up and be take the Optimal Operation Model that total system cost of electricity-generating minimum is target; Using 15 minutes logic periods as an optimization, using dispatching cycle internal loading prediction curve as research object, in conjunction with producing and turnaround plan, optimize enterprises and can dispatch exerting oneself of genset, optimization aim is enterprise's self power generation cost minimization.

Iron and steel enterprise's cost of electricity-generating Optimized model is, objective function:

$\min C_{\cos t}=\underset{t}{\mathrm{\Σ}}(\underset{i=1}{\overset{K}{\mathrm{\Σ}}}{C}_{\mathrm{zf}(i,t)}+C_{\mathrm{wg}}-C_{\mathrm{ws}})$

Constraint condition:

$C_{\mathrm{wg}}=\underset{t}{\mathrm{\Σ}}{P}_{w,t}\×C_t\×{\mathrm{\δ}}_t$

$C_{\mathrm{ws}}=\underset{t}{\mathrm{\Σ}}{P}_{\mathrm{ws},t}\×C_s\×{\mathrm{\σ}}_t$

$\underset{i=1}{\overset{K}{\mathrm{\Σ}}}{P}_{i,t}+P_{w,t}=P_{\mathrm{load},t}$

P _i,min≤P _i,t≤P _i,max

-UR _i≤P _i,t-P _i,t-1≤UR _i,i＝1,2...K

$P_{\mathrm{ij},t}=\underset{i\∈M}{\mathrm{\Σ}}[P(i,t)-S_{i,t}]{\mathrm{\ω}}_{i,j,t}$

P _ij,min≤P _ij,t≤P _ij,max

$P_{w,\min }\≤\underset{t=1}{\overset{24}{\mathrm{\Σ}}}{P}_{w,t}\≤P_{w,\max }$

Wherein, K is schedulable power plant for self-supply genset number in enterprise, and N is the time hop count comprising in system dispatching cycle T, C _{zf (i, t)}be the self power generation cost of i platform unit t period, C _wgouter power purchase cost, P _w,touter purchase of electricity, C _tfor the outsourcing electricity price of t period, δ _tbe that 0,1 scale is levied and had or not outer power supply, C _wsouter power transmission income, P _{ws, t}send electric weight outside, C _sfor sending electricity price outside, σ _tbe that 0,1 scale is levied without outer power transmission, P _i,tfor meritorious the exerting oneself of i platform unit t period, P _{load, t}for t period enterprise load prediction value, P _{i, min}, P _{i, max}be respectively unit i and exert oneself and bound ,-UR _i, UR _ifor per period of unit i can load increase and decrease maximal value (climbing capacity of unit), P _{ij, t}for branch road ij at t the trend on the time period, P (i, t) is node i at the injecting power of t time period, M is the supervision parts number comprising under node i, S _i,tfor node load power, ω _{i, j, t}for node injecting power to branch road ij at t the influence coefficient on the time period, P _{ij, min}, P _{ij, max}the bound that represents branch road ij trend, P _{w, min}, P _{w, max}do not represent the confession purchase of electricity bound that generator i is determined by contract in time T;

Step 5, according to Optimization Solution, obtaining enterprise's self generating sets exerts oneself, outer purchase of electricity, send the result of electric weight outside, consider that overall network monitors element, carries out Security Checking to day part, if not newly-increased, monitor that element voltage or electric current are out-of-limit, enter step 6, otherwise calculate the influence coefficient information of newly-increased out-of-limit supervision element, then enter step 2;

Step 6, iteration finishes, and draws iron and steel enterprise's self power generation plan, optimizes and finishes, and provides the self power generation scheme of cost minimization.

The invention has the beneficial effects as follows:

The iron and steel enterprise's cost of electricity-generating Optimization Scheduling that adopts the present invention to propose, can arranged rational the generation schedule of following enterprise private station, the present invention has considered enterprise's self power generation, outer power purchase, outer power transmission for the impact of cost of electricity-generating, consider the various constraint conditions such as Constraints of Equilibrium, the constraint of genset self-operating, outsourcing Constraint and electric power netting safe running constraint when system is moved a few days ago simultaneously, guaranteed the enforceability of generation schedule; Taking into account system load prediction curve of the present invention, production maintenance plan, Pinggu, outer power purchase peak electricity price gap, the situations such as outer power transmission income, optimize the plan of exerting oneself of enterprise's self generating sets, guaranteed that enterprise's private station stablizes economical operation under prerequisite meeting security of system.

Iron and steel enterprise's cost of electricity-generating Optimization Scheduling that the present invention proposes, can arranged rational the generation schedule of following enterprise private station, the present invention has considered enterprise's self power generation, outer power purchase, outer power transmission for the impact of cost of electricity-generating, consider the various constraint conditions such as Constraints of Equilibrium, the constraint of genset self-operating, outsourcing Constraint and electric power netting safe running constraint when system is moved a few days ago simultaneously, guaranteed the enforceability of generation schedule; Taking into account system load prediction curve of the present invention, production maintenance plan, Pinggu, outer power purchase peak electricity price gap, the situations such as outer power transmission income, optimize the plan of exerting oneself of enterprise's self generating sets, guaranteed that enterprise's private station stablizes economical operation under prerequisite meeting security of system.

Above embodiment is used for illustrative purposes only, it is not limitation of the present invention, person skilled in the relevant technique, without departing from the spirit and scope of the present invention, can make various conversion or modification, therefore, all technical schemes that are equal to also should belong to category of the present invention, should be limited by individual claim.

Claims (1)

1. The method that 1.Yi Zhong iron and steel enterprise cost of electricity-generating is optimized, is characterized in that, comprises the following steps:

   Step 1, determine T dispatching cycle that need to carry out cost of electricity-generating optimization, obtain unit generation cost optimization parameter, these parameters comprise: enterprise's load prediction curve, production and turnaround plan, the plan of outsourcing power transmission, the start and stop state of unit, upstate, the plan of exerting oneself of fixing genset in dispatching cycle, adjust unit output plan;

   Step 2, obtain the network section for generation schedule establishment a few days ago, network section refers to the one group of transmission line of electricity that is mutually related in power grid security or electric weight transaction, simultaneously in conjunction with enterprise's production maintenance plan, utilize electric network model automatically to generate the network topology of day part, and calculate the trend distribution of day part and monitor element influence coefficient;

   Step 3, determine that in the cycle, consideration coal gas is mixed the genset fuel cost in burning situation:

   $C_{\mathrm{zf}}=\underset{t=1}{\overset{N}{\mathrm{\Σ}}}[F{\left(P\right)}_{i,t}\×C_{i,t}^f]$

   F(P) _i,t＝aP _i,t ²+bP _i,t+c

   $C_{i,t}^f=C^{\mathrm{coal}}\×\frac{Q^B}{Q^{\mathrm{coal}}}\×Y_{i,t}^{\mathrm{coal}}+C^{\mathrm{bfg}}\×\frac{Q^B}{Q^{\mathrm{bfg}}}\×Y_{i,t}^{\mathrm{bfg}}+C^{\mathrm{cog}}\×\frac{Q^B}{Q^{\mathrm{cog}}}\×Y_{i,t}^{\mathrm{cog}}$

   Wherein, C _zffor genset fuel cost, F (P) _i,tbe the mark coal consumption of i platform unit t period, P _i,tbe meritorious the exerting oneself of i platform unit t period,

   

   be the fuel unit price of i platform unit t period coal and coal gas mixed combustion, C ^coal, C ^bfg, C ^cogbe respectively outsourcing coal, blast furnace gas, the price of coke-oven gas; Q ^coal, Q ^bfg, Q ^cogbe respectively coal, blast furnace gas, the calorific value of coke-oven gas; Q wherein ^bfor mark coal calorific value, its value is constant is 29308KJ/Kg; be respectively i platform unit t period coal, blast furnace gas, coke-oven gas accounts for the ratio of total fuel heat;

   Consider that coal gas is mixed in the existing system of situation ，Cong enterprise of burning and read coal, blast furnace gas, the amount of coke-oven gas with and corresponding the meritorious of unit exert oneself, by coal, blast furnace gas, coke-oven gas is amounted to into mark coal amount, and then matching obtains the units consumption model F (P) in one-period T _i,t=aP _i,t ²+ bP _i,t+ c is a wherein, b, and c is fitting coefficient;

   Step 4, according to enterprise's units consumption, outer power purchase cost and outer power transmission income actual conditions are set up and be take the Optimal Operation Model that total system cost of electricity-generating minimum is target; Using 15 minutes logic periods as an optimization, using dispatching cycle internal loading prediction curve as research object, in conjunction with producing and turnaround plan, optimize exerting oneself of enterprises scheduling genset, optimization aim is enterprise's self power generation cost minimization;

   Iron and steel enterprise's cost of electricity-generating Optimized model is, objective function:

   $\min C_{\cos t}=\underset{t}{\mathrm{\Σ}}(\underset{i=1}{\overset{K}{\mathrm{\Σ}}}{C}_{\mathrm{zf}(i,t)}+C_{\mathrm{wg}}-C_{\mathrm{ws}})$

   Constraint condition:

   $C_{\mathrm{wg}}=\underset{t}{\mathrm{\Σ}}{P}_{w,t}\×C_t\×{\mathrm{\δ}}_t$

   $C_{\mathrm{ws}}=\underset{t}{\mathrm{\Σ}}{P}_{\mathrm{ws},t}\×C_s\×{\mathrm{\σ}}_t$

   $\underset{i=1}{\overset{K}{\mathrm{\Σ}}}{P}_{i,t}+P_{w,t}=P_{\mathrm{load},t}$

   P _i,min≤P _i,t≤P _i,max

   -UR _i≤P _i,t-P _i,t-1≤UR _i,i＝1,2...K

   $P_{\mathrm{ij},t}=\underset{i\∈M}{\mathrm{\Σ}}[P(i,t)-S_{i,t}]{\mathrm{\ω}}_{i,j,t}$

   P _ij,min≤P _ij,t≤P _ij,max

   $P_{w,\min }\≤\underset{t=1}{\overset{24}{\mathrm{\Σ}}}{P}_{w,t}\≤P_{w,\max }$

   Wherein, K is schedulable power plant for self-supply genset number in enterprise, and N is the time hop count comprising in system dispatching cycle T, C _{zf (i, t)}be the self power generation cost of i platform unit t period, C _wgouter power purchase cost, P _w,touter purchase of electricity, C _tfor the outsourcing electricity price of t period, δ _tbe that 0,1 scale is levied and had or not outer power supply, C _wsouter power transmission income, P _{ws, t}send electric weight outside, C _sfor sending electricity price outside, σ _tbe that 0,1 scale is levied without outer power transmission, P _i,tfor meritorious the exerting oneself of i platform unit t period, P _{load, t}for t period enterprise load prediction value, P _{i, min}, P _{i, max}be respectively unit i and exert oneself and bound ,-UR _i, UR _ifor per period of unit i can load increase and decrease maximal value, P _{ij, t}for branch road ij at t the trend on the time period, P (i, t) is node i at the injecting power of t time period, M is the supervision parts number comprising under node i, S _i,tfor node load power, ω _{i, j, t}for node injecting power to branch road ij at t the influence coefficient on the time period, P _{ij, min}, P _{ij, max}the bound that represents branch road ij trend, P _{w, min}, P _{w, max}do not represent the confession purchase of electricity bound that generator i is determined by contract in time T;

   Step 5, according to Optimization Solution, obtaining enterprise's self generating sets exerts oneself, outer purchase of electricity, send the result of electric weight outside, consider that overall network monitors element, carries out Security Checking to day part, if not newly-increased, monitor that element voltage or electric current are out-of-limit, enter step 6, otherwise calculate the influence coefficient information of newly-increased out-of-limit supervision element, then enter step 2;

   Step 6, iteration finishes, and draws iron and steel enterprise's self power generation plan, optimizes and finishes, and provides the self power generation scheme of cost minimization.